MULTIMEDIA SECURITY & BIOMETRY

Academic Year 2024/2025 - Teacher: ALESSANDRO ORTIS

Expected Learning Outcomes

By the end of the course, students will be able to understand the fundamentals of biometrics, including its history and applications. They will be able to apply recognition techniques for fingerprints, faces, and irises, and address the challenges associated with these technologies. Students will also be familiar with soft biometrics and know how to integrate multiple biometric modalities into multibiometric systems. Additionally, they will be able to ensure the security of biometric data by recognizing threats and implementing protective measures. Finally, they will develop advanced technical skills through practical projects and case studies.

Course Structure

The course will alternate between lectures and in-depth explorations of specific applications to provide a clear connection between theoretical concepts and their practical application.

Required Prerequisites

Understanding of fundamental concepts such as algorithms, data structures, and programming. Basic knowledge of linear algebra, probability, and statistics. Basic concepts of digital signal processing, including image and audio processing techniques. Introductory knowledge of information security principles and practices. Proficiency in an object-oriented programming language.

Attendance of Lessons

Attendance optional but strongly recommended

Detailed Course Content

This course provides an introduction to biometric technologies and their applications in multimedia security. Topics covered include various biometric modalities such as fingerprint, face, and iris recognition, as well as soft biometrics and multibiometrics. Additionally, the course will address the security aspects of biometric systems.

Introduction to Biometrics

Definition and scope of biometrics
History and evolution of biometric technologies
Applications of biometrics in security and authentication
Performance evaluation and recognition reliability

Fingerprint Recognition

Anatomy of fingerprints
Fingerprint acquisition techniques
Fingerprint matching algorithms
Challenges and limitations in fingerprint recognition

Face Recognition

Fundamentals of face recognition
Detection and extraction of facial features
Face matching algorithms
Face recognition under varying conditions (e.g., lighting, pose)

Iris Recognition

Anatomy of the human iris
Iris image acquisition methods
Iris recognition algorithms
Advantages and challenges of iris recognition

Soft Biometrics

Definition and characteristics of soft biometrics
Types of "soft" biometric traits
Applications of soft biometrics in multimedia security

Multibiometrics

Integration of multiple biometric modalities
Benefits and challenges of multibiometrics
Multimodal fusion techniques
Case studies on successful multibiometric systems

Security of Biometric Systems

Threats and vulnerabilities in biometric systems
Techniques for protecting biometric data
Spoofing attacks and countermeasures
Ethical and privacy considerations in biometrics

Textbook Information

Jain, Anil K., Patrick Flynn, and Arun A. Ross, eds. Handbook of biometrics. Springer Science & Business Media, 2007.

Anil K. Jain , Arun A. Ross , Karthik Nandakumar, Introduction to Biometrics, Springer, 2011

Course Planning

	Subjects	Text References
1	Introduction	Ch 1
2	Fingerprint recognition	Ch 2
3	Face recognition	Ch 3
4	Iris recognition	Ch 4
5	Additional biometric traits	Ch 5
6	Multibiometrics	Ch 6
7	Security in biometric systems	Ch 7
8	Biometrics and AI	Additional material

Learning Assessment

Learning Assessment Procedures

Knowledge will be assessed through an oral examination. Students have the opportunity to undertake a project related to one or more course topics, to be agreed upon with the instructor.

The assessment of learning may also be conducted online, should the circumstances require it. Students with disabilities and/or specific learning disorders (SLD) must contact the professor and the CInAP representative of the Department of Mathematics and Computer Science (DMI) well in advance of the exam date to inform them of their intention to take the exam with the appropriate compensatory measures

Examples of frequently asked questions and / or exercises

What are the types of minutiae in fingerprints?

Degree Course in

Computer Science